Our AI is learning to read minds. Or the next best thing: a company's Chart of Accounts. On Day 13 of Vibe Accounting we discovered something interesting about semantic understanding in accounting AI.
Our agent is hitting 95% accuracy on GL account suggestions from raw transaction data. We feed it messy descriptions, SKUs, vendor names - the usual chaos - and it consistently picks the right account.
But the fascinating part isn't the accuracy. It's how the AI is reasoning. The system is reverse-engineering each company's financial philosophy from their chart of accounts that are fed as context.
Same transaction, three different companies. Let's say we have the following transaction: "Stripe processing fees - $2,847":
It nails all three because it's not just matching keywords, it’s deciphering each company's strategic DNA from their existing books. It's inferring business strategy from account structures.
The 5% of errors? Those are the genuinely ambiguous cases where even human accountants would need to ask around.
This means the accountant's role is shifting from manually coding transactions to teaching the AI how their business speaks the language of money.